关键词: 人脸识别, 灰度归一化, 特征脸, 姿态估计, 加权最小距离分类器

Abstract: The influences of pose and illumination variations are two major bottlenecks toward full automatic face recognition.A novel method which handles both pose and lighting conditions is proposed here via this paper.First，the intensity of images in training set is normalized in order to reduce the susceptivity toward lighting intensity.Afterwards，the images’ pose is estimated，and eigenvector subspace of different pose is built up by means of eigenface.Ultimately，the conception called PWV（Pose’s Weight Value） is proposed for a new classification WMDC（Weighted Minimum Distance Classifier），which is designed according to normalized Euclidian distance.Due to this approach，the problem of variant pose is solved by assigning different pose’s weight value.Experimental results on FERET and Yale B database demonstrate that this technique can significantly improve the accuracy of face recognition under variant illumination and pose conditions.

Key words: face recognition, intensity normalization, eigenface, pose estimation, weighted minimum distance classifier